﻿README File 
Tracking of North Carolina Legal Statutes: Fines and Fees Dataset - Version 2




Description
The updated North Carolina Legal Statutes: Fines and Fees Dataset (Version 2) provides comprehensive and detailed information about legal statutes in North Carolina, specifically focusing on associated fines and fees. This dataset includes expanded data on the amounts, years of changes, levels of offenses, penalty types, and the funds where the money was allocated. It covers a broader range of years than the initial release, reflecting both historical and recent changes in legal financial obligations (LFOS) within the state.
Collection Methodology
Data for this updated dataset was collected from various reliable sources, primarily the North Carolina State code and crosschecked with LexisNexis State (now Lexis Uni) database.
Data Dictionary (with Example Entries)
The Data Dictionary is expanded to include new columns and details based on the updated dataset:
Column Name
	Description
	Example from Updated Dataset
	Statute ID
	Unique identifier for each statute
	nc_1
	Fee ID
	Unique identifier for each fee associated with a statute
	nc_1_1
	Year
	Year of the statute or fee change
	1997
	Level of Offense
	Categorization of the offense (e.g., Misdemeanor, Felony)
	Misdemeanor
	Penalty Type
	Type of financial obligation (e.g., Flat Fee, Variable Fee)
	Flat Fee
	Penalty Type - Notes
	Additional notes on the penalty type
	Service fee for each arrest...
	Fee Minimum Value
	Minimum value of the fee, if applicable
	$5
	Fee Maximum Value
	Maximum value of the fee, if applicable
	$10
	Fee Fixed Amount
	Fixed amount of the fee, if applicable
	$5
	Fee Other
	Other forms or details of the fee
	Restitution
	Other Data Collection Notes
	Additional notes relevant to the data collection or statute
	For each arrest or personal service...
	

Note: At times, there may be interchangeable usage of the time “fee” to describe a monetary sanction, when in fact, the fee may refer to a surcharge or fine. We have done our best to find these discrepancies, and any subsequent corrections will be made in the next release.




Glossary
Glossary of Terms for  Fee ID Abbreviations
Abbreviation
	Meaning
	Example
	r
	Repealed
	tx_12_r - clerk of the court fee
	m
	misdemeanor
	hi_40_md5 -  human trafficking victim services; misdemeanor
	f
	Felony
	hi_40_fca2 - human trafficking victim services; class a felony. (fca = class a felony)
	o
	Offense
	njj_11_o1 - fine for disorderly persons offense
	d
	Degree
	nj_7_d1 - fine for first degree crime
	c
	Class
	ny_2_mvca1 - fines for misdemeanors and violation (class a) - (mvca = misdemeanor and violation class a)
	v
	Violation
	hi_9_v1 - first violation of an order for protection
	jl
	Juvenile Law
	tx_8_jv1 - court costs for parent contributing to truancy
	dc
	District Court
	nc_2_dc1 - for the use of the courtroom and related judicial facilities, the sum of twelve dollars ($12.00) in the district court, including cases before a magistrate.
	sc
	Superior Court
	nc_2_sc1 - the sum of thirty dollars ($30.00) in superior court, to be remitted to the county where the judgment is rendered.
	u
	Unclassified
	or_5_uv2 - The amount otherwise established by law for any specific fine violation - (uv = unclassified violation)
	

Data Processing
The data processing steps for this updated version include:
Handling Missing Values: Missing values, especially in columns representing fee amounts and years, were carefully handled, either filled with zeros or annotated for further research, ensuring completeness.
Data Type Conversion and Validation: Numeric values, especially fee amounts, were validated and converted to ensure accuracy and consistency.
Standardization of Categories and Codes: New categories such as "Level of Offense" and "Penalty Type" were standardized across the dataset for consistency.
Date and Year Processing: Validation of year columns was conducted to ensure chronological accuracy and consistency.
Text Preprocessing: Textual data, particularly in "Penalty Type - Notes" and "Other Data Collection Notes," were preprocessed for clarity and uniformity.
Normalization of Amounts: Where applicable, fee amounts were normalized or standardized for comparative analysis.
Handling Special Cases: Special attention was given to statutes with complex fee structures or unique conditions.
Quality Assurance and Validation: Rigorous quality checks were performed to ensure the accuracy and reliability of the data.
Exporting and Formatting: The final dataset was formatted for ease of use and analysis, preserving all data types and Data Processing


For the updated dataset, the following data processing steps were implemented:
Handling Missing Values: Missing values, especially in columns representing fee amounts, years, and funds, were carefully filled with appropriate placeholders or estimates based on available information to maintain dataset integrity.
Data Type Conversion and Validation: Numeric values, particularly fee amounts, were meticulously converted and validated to ensure accuracy and consistency.
Standardization of Categories and Codes: Categories like "Level of Offense", "Penalty Type", and "Mandatory" were standardized to ensure uniformity across the dataset.
Date and Year Processing: Year columns were thoroughly checked and validated for consistency, and any discrepancies were rectified.
Text Preprocessing: Textual data, such as those in "Statutory Language" and "Description/Statute Name," underwent preprocessing to remove extraneous spaces, correct typographical errors, and standardize terminology.
Normalization of Amounts: The fee amounts were normalized to facilitate comparison across different statutes and time periods.
Handling Special Cases: Specific methods were applied to handle unique cases, such as fees stated as "cost" or represented as a range.
Quality Assurance and Validation: A comprehensive quality check was conducted to confirm the accuracy and consistency of the data post-transformation.
Exporting and Formatting: The dataset was exported in a user-friendly format, preserving all data types and ensuring readability.
Documentation: All data processing steps, methodologies, and decision rationales were thoroughly documented.
Intended Use
This expanded dataset is intended for use in various fields, including:
* Legal Analysis: Enabling researchers and legal professionals to delve into trends and patterns in fee adjustments over time.
* Government Oversight: Assisting regulatory bodies and policymakers in understanding the allocation and impacts of fines and fees.
* Academic Research: Providing a resource for scholars in law, economics, social sciences, and related fields for in-depth studies.
* Public Awareness: Facilitating journalists and advocacy groups to highlight the legal and financial dynamics in North Carolina.
Limitations
The following limitations should be considered when utilizing this dataset:
* Data Source Reliability: The dataset is based on information from NexisUni and the North Carolina State code, which may have inherent limitations when data has yet to be digitized.
* Handling of Ranges: Fees represented as ranges were averaged, which may not fully reflect the diversity of the fee structure.
* Filled Missing Values: Some missing values were filled with placeholders or estimates, which might not capture the exact situation. That is especially true in instances where there were no monetary sanctions listed.
* Potential Inconsistencies: Despite rigorous efforts to standardize and validate the data, minor inconsistencies or overlooked errors might still exist.
Upcoming Version Notice
Future updates to this dataset are planned, including additional financial sanctions and data extending beyond the current scope. Users interested in the most comprehensive view should look for these updates.
Contact and Support
For inquiries or support related to this dataset, please contact Dr. Tauheeda Yasin at tauheeda.yasin@austin.utexas.edu or tauheeda.yasin@gmail.com. For information on the Justice Funding Database please see: tauheedayasinmartin.com/justice-funding-database


License
This dataset is available under the CC BY 4.0 license.
FAQs
Q: How has this dataset been expanded in Version 2 compared to Version 1?
A: Version 2 introduces additional statutes and fees, extends year coverage, and incorporates expanded columns like 'Level of Offense' and 'Penalty Type.' The dataset now provides a more detailed and holistic view of the legal financial landscape in North Carolina.


Q: Can this dataset be used to compare legal fines and fee changes over a long time?
A: Yes, the dataset is structured to support longitudinal analysis, enabling researchers to track and compare changes in fines and fees over several years. This allows for a deeper understanding of trends and policy impacts.


Q: What measures have been taken to ensure the accuracy of the data in Version 2?
A: Version 2 underwent extensive data validation and quality assurance processes, including cross-referencing with official legal codes, standardizing categories and terminologies, and rigorous checks for data consistency for seven months.


Q: Is the dataset suitable for interdisciplinary research?
A: Absolutely. The comprehensive dataset makes it an excellent resource for interdisciplinary research, bridging legal studies with sociology, economics, public policy, and more.


Q: How can I contribute to or collaborate on future versions of this dataset?
A: Please contact Dr. Tauheeda Yasin for collaboration or contributions at the provided details. We welcome academic and research contributions that can enhance the dataset's depth and breadth, especially regarding work that can lead to more effective policy and decision-making.


Q: Are there any specific considerations when using this dataset for policy analysis?
A: Users should consider the dataset's limitations, such as handling fee ranges and filled missing values. Additionally, understanding the context of each statute within the broader legal and social framework of North Carolina is crucial for policy analysis.


Q: Will future versions include data beyond monetary fines and fees?
A: Future versions aim to encompass a more comprehensive array of legal financial obligations and sanctions, providing an even more comprehensive view of the legal landscape in municipal courts.